12 citations · 30 across the 16 of their papers we have counts for
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cs.AI2024
CRoP: Context-wise Robust Static Human-Sensing Personalization
Sawinder Kaur, Avery Gump, Yi Xiao +5
The advancement in deep learning and internet-of-things have led to diverse human sensing applications. However, distinct patterns in human sensing, influenced by various factors o…
cs.LG2024
CurvFed: Curvature-Aligned Federated Learning for Fairness without Demographics
Harshit Sharma, Shaily Roy, Asif Salekin
Modern human sensing applications often rely on data distributed across users and devices, where privacy concerns prevent centralized training. Federated Learning (FL) addresses th…
cs.CV2024
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models
Weiheng Chai, Brian Testa, Huantao Ren +2
Deep neural networks are extensively applied to real-world tasks, such as face recognition and medical image classification, where privacy and data protection are critical. Image d…